1. Technical Field
The present invention is directed to the optimization of building energy use and, more particularly, to an improved optimization configuration whereby the building automation system, an energy simulation software package and an optimization engine work in concert with one another to examine variables relating to operational and environmental temperature values and cooperatively optimize those variables to generate setpoints for the building systems to reduce the building HVAC system's operational costs and increase the operating efficiency of the heating/cooling system of the building.
2. Description of the Prior Art
The need for more efficient and sustainable buildings has grown as the number of buildings being built and renovated continues to rise in the presence of sharply rising energy costs. Building owners react to increasing utility costs by demanding better designs from engineering professionals yet standard practice has inherent limitations to the overall benefit that can be provided building owners. Accordingly the HVAC industry has attempted to develop HVAC optimization systems and techniques that allow the building owner to reduce energy costs, a long-felt need which has yet to be fully addressed.
The prior art discloses that in a majority of the optimization techniques reviewed each control loop is optimized independently of the other control loops, hence the label “subsystem optimization”. For example, one technique might involve optimizing the chilled water plant independent of the air-handling unit (AHU). While this allowed for a generic or “one size fits all” approach, there are inherent problems in this approach which do not fully address and solve the need for optimization and efficiency demanded in today's market. For example, the prior art approach described above will often result in control loops acting against one another, as the independent optimization of the control loops commands, as when the optimization system resets the chilled water temperature to reduce chiller energy consumption without recognizing the impact on the air handler unit (AHU).
Subsystem optimization by its very nature encourages each subsystem to reduce its workload without recognizing that if certain systems are pushed harder to enable other systems to work even less additional savings are possible. In fact, some subsystems can be pushed beyond their design load due to a factor attributable to the manufacturing process. For example, if a chiller requires a 67 horsepower motor to meet the design load, the manufacturer is going to install a 75 horsepower motor because it is the next larger size available. The project electrical engineer in turn has to size the electrical service to serve this motor by code.
Therefore, there is a need for an integrated/comprehensive view of building energy consumption based on system capacities that can adapt to any HVAC system configuration and yet is independent of proprietary features of a specific manufacturer's equipment.
The prior art also discloses that some optimization techniques utilize room setpoint changes to minimize energy costs (usually by reducing demand). Room setpoint, generally, is not the best indicator of efficiency of the HVAC system, but rather is indicative of the comfort level within the building. Therefore, it is not the best device by which to effectuate optimization of efficiency, and therefore is best not included as one of the interactive loops in an optimization system.
The prior art also discloses that some optimization techniques involve the direct reprogramming of automation controllers for global optimization techniques. While this allowed for self-contained programming, there are inherent problems such as the computing load placed on building automation controllers, the difficulty of executing intricate predictive programming in control processors and the programming of software made for feedback applications. Therefore there is a need to migrate the information into an environment built for generation of energy utilization estimates.
The prior art also discloses that some optimization techniques involve supervisory control such as artificial neural network (ANN) supervision of automation controllers for global optimization techniques. ANNs utilize fundamentally different logic than is shown in the present invention. ANNs have many additional applications not related to building energy optimization and differ in concept from the present invention. Prior research has shown that commercial ANN-based products can successfully save energy in buildings, but the present invention will not feature nor discredit ANN algorithms. Historically, the building industry has not widely accepted optimization featuring artificial neural networks, but its usability was not examined here due to the basic difference in approach as compared to the present invention. It is an object of the invention be an improved and relatively simple optimization configuration and ANN-based approaches represent a smaller niche of techniques which do not compare directly in line with the present invention.
There is therefore a need to:
1. Determine another method for predicting energy usage.
2. Determine a method that is simple to use, from the building engineer to the contractor to the owner.
3. Execute the evaluation quickly.
The prior art also discloses applications which optimize chiller plants serving manufacturing facilities by utilizing supervisory control. The first feature of the prior art that introduces some inaccuracy into the energy savings calculation is the reliance on weather forecasts. Not only do the weather prediction tools have an associated inaccuracy but there are also questions regarding the correlation of a “local” forecast with the actual site conditions impacting variables. For example, if an AHU is sitting on a black roof on a summer day, the intake air may be far warmer than the selected forecast value.
The second feature of the prior art that introduces some inaccuracy into the energy savings calculation is the reliance on predicted load. While it may be possible to accurately predict the load on a manufacturing plant where a significant majority of the load is due to equipment that is operating on a 24/7 basis, other facilities have a much more diverse profile including elements such as solar loading, equipment, lights and people which do change significantly between weekday and weekend profiles. These prior art applications also appear to focus on finding the most efficient chiller staging scenario without extending the analysis to consider variations in chiller/condenser setpoints. And, last but not least, these applications were limited to only considering the optimization of the plant without extending the analysis to consider the impact of the AHU on the total energy balance as well as any system-limiting factors generated by the air terminal units typically found in most AHU systems. Therefore, there is a need to utilize real-time weather and load information to improve the accuracy of the calculation.
Therefore, an object of the present invention is to provide an improved energy optimization system for use with heating and cooling systems for buildings.
Another object of the present invention is to provide an improved energy optimization system which will examine variables relating to operational and environmental temperature values and cooperatively optimize those variables to generate setpoints for the building systems to reduce the building HVAC system's operational costs and increase the operating efficiency of the heating/cooling system of the building.
Another object of the present invention is to provide an improved energy optimization system which works in cooperation with the building automation system to ensure compatibility with building systems generally regardless of the manufacturer.
Another object of the present invention is to provide an improved energy optimization system which simultaneously optimizes the input water temperature (IWT) of said heating/cooling system prior to adjustment of the water temperature, the output water temperature (OWT) after adjustment of the water temperature by said heating/cooling system and the supply air temperature (SA) output to the building via the at least one air handling unit to increase the operating efficiency of the heating/cooling system of the building.
Finally, an object of the present invention is to provide an improved energy optimization system which is relatively simple and straightforward in implementation and is safe, efficient and effective in operation.